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Operations Research, Systems Engineering and Industrial Engineering Commons™
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- Keyword
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- Vehicle routing problem (3)
- Reinforcement learning (2)
- Airport ground handling (1)
- Attention model (1)
- Bacteria-based self-healing (1)
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- Best response planning (1)
- Capacitated vehicle routing problem (1)
- Clockwise clustering (1)
- Decomposition-composition (1)
- Durability of concrete structures (1)
- Electric vehicle charging (1)
- Electric vehicles (1)
- Expectation-maximization (1)
- Experimental tests (1)
- Express service (1)
- Heuristic methods (1)
- Imitation learning (1)
- Improvement learning (1)
- Incomplete observations (1)
- Memetic algorithm (1)
- Mixed backhauls (1)
- Mixed integer programming (1)
- Multi-agent systems (1)
- Nested recursive logit (1)
- Operation research (1)
- Optimization (1)
- Predictive models (1)
- Recursive logit (1)
- Ridesharing (1)
- Self-healing concrete (1)
Articles 1 - 10 of 10
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang
Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang
Research Collection School Of Computing and Information Systems
Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …
Estimation Of Recursive Route Choice Models With Incomplete Trip Observations, Tien Mai, The Viet Bui, Quoc Phong Nguyen, Tho V. Le
Estimation Of Recursive Route Choice Models With Incomplete Trip Observations, Tien Mai, The Viet Bui, Quoc Phong Nguyen, Tho V. Le
Research Collection School Of Computing and Information Systems
This work concerns the estimation of recursive route choice models in the situation that the trip observations are incomplete, i.e., there are unconnected links (or nodes) in the observations. A direct approach to handle this issue could be intractable because enumerating all paths between unconnected links (or nodes) in a real network is typically not possible. We exploit an expectation–maximization (EM) method that allows dealing with the missing-data issue by alternatively performing two steps of sampling the missing segments in the observations and solving maximum likelihood estimation problems. Moreover, observing that the EM method could be expensive, we propose a …
Electrical Vehicle Charging Infrastructure Design And Operations, Yu Yang, Hen-Geul Yeh
Electrical Vehicle Charging Infrastructure Design And Operations, Yu Yang, Hen-Geul Yeh
Mineta Transportation Institute
California aims to achieve five million zero-emission vehicles (ZEVs) on the road by 2030 and 250,000 electrical vehicle (EV) charging stations by 2025. To reduce barriers in this process, the research team developed a simulation-based system for EV charging infrastructure design and operations. The increasing power demand due to the growing EV market requires advanced charging infrastructures and operating strategies. This study will deliver two modules in charging station design and operations, including a vehicle charging schedule and an infrastructure planning module for the solar-powered charging station. The objectives are to increase customers’ satisfaction, reduce the power grid burden, and …
Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai
Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai
Research Collection School Of Computing and Information Systems
Recent works using deep reinforcement learning (RL) to solve routing problems such as the capacitated vehicle routing problem (CVRP) have focused on improvement learning-based methods, which involve improving a given solution until it becomes near-optimal. Although adequate solutions can be achieved for small problem instances, their efficiency degrades for large-scale ones. In this work, we propose a newimprovement learning-based framework based on imitation learning where classical heuristics serve as experts to encourage the policy model to mimic and produce similar or better solutions. Moreover, to improve scalability, we propose Clockwise Clustering, a novel augmented framework for decomposing large-scale CVRP into …
Optimization Of Station-Skip In A Cyclic Express Subway Service, Jingfeng Yang, Hai Wang, Jiangang Jin
Optimization Of Station-Skip In A Cyclic Express Subway Service, Jingfeng Yang, Hai Wang, Jiangang Jin
Research Collection School Of Computing and Information Systems
With rapid population growth and increasing demand for urban mobility, metropolitan areas such as Singapore, Tokyo, and Shanghai are increasingly dependent on public transport systems. Various strategies are proposed to improve the service quality and capacity of bus and subway systems. Express trains—i.e., trains that skip certain stations—are commonly used because they can travel at higher speeds, potentially reduce travel time, and serve more passengers. In this paper, we study cyclic express subway service (CESS), in which express trains provide routine transport service with cyclic (periodic) station-skip patterns that can be used in daily service. We propose an exact Mixed …
Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto
Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto
Research Collection School Of Computing and Information Systems
Recent technological developments—mobile computing, autonomous driving, alternative fuel vehicles, and blockchain, to name a few—have enabled numerous innovations in mobility, transportation, and logistics services. They offer unprecedented opportunities to transform conventional transportation systems, for both personal travel and freight logistics, with novel solutions. Of these solutions, those built on the emerging concept of shared economy, such as Uber, Didi, and Cargostream, have received much attention recently. The rapidly expanding scope of shared transportation services now includes ride-sourcing, ridesharing, car sharing, hitch service, flexible paratransit, shared freight delivery, shared logistics, bike sharing, shared last-mile service, parking space sharing, and so on.
Experimental Investigation Of The Self-Healing Potential Of Bacteria For Sustainable Concrete Structures, Pitiporn Asvapathanagul, Simone Galano, Andrea Calabrese, Mehran Rahmani, Maggie Ly, Daniela Flores, Michael Hernandez, Nicholas Banuelos
Experimental Investigation Of The Self-Healing Potential Of Bacteria For Sustainable Concrete Structures, Pitiporn Asvapathanagul, Simone Galano, Andrea Calabrese, Mehran Rahmani, Maggie Ly, Daniela Flores, Michael Hernandez, Nicholas Banuelos
Mineta Transportation Institute
Although concrete is the most widely used building material in the world, its limited tensile strength makes cracking a common phenomenon in concrete elements. This study investigates the potential of autonomous self-healing as an eco-friendly and lowcost method to increase the durability of concrete. The crack-healing potential of different types of high-alkaline-tolerant bacteria or calcite-precipitation microorganisms is investigated. High-alkaline-tolerant bacteria and calcite-precipitation microorganisms were used to retrofit lab-fractured concrete samples. The samples healed with each of these bacteria groups were cast and tested under compressive load up to failure to measure the compressive strength of the concrete samples. The outcomes …
Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar
Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar
Research Collection School Of Computing and Information Systems
Rapid developments in city infrastructure and technol-ogies are creating numerous opportunities and inspiring innovative and emerging urban services. Among these innovations, complex systems of urban transportation and logistics have embraced advances and have been reshaped significantly. They enable innovative new urban services, which are now booming and changing everyday life for urban residents.This special issue of Service Science explores perspectives on innovation in transportation-enabled urban services. We hope that the special issue will enhance the understanding of the planning, operation, and management of such services. Contributions are expected to demonstrate rigorous model development, economic/ econometric analysis, and decision-making tools based …
Coordinating Multi-Party Vehicle Routing With Location Congestion Via Iterative Best Response, Waldy Joe, Hoong Chuin Lau
Coordinating Multi-Party Vehicle Routing With Location Congestion Via Iterative Best Response, Waldy Joe, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This work is motivated by a real-world problem of coordinating B2B pickup-delivery operations to shopping malls involving multiple non-collaborative logistics service providers (LSPs) in a congested city where space is scarce. This problem can be categorized as a vehicle routing problem with pickup and delivery, time windows and location congestion with multiple LSPs (or ML-VRPLC in short), and we propose a scalable, decentralized, coordinated planning approach via iterative best response. We formulate the problem as a strategic game where each LSP is a self-interested agent but is willing to participate in a coordinated planning as long as there are sufficient …
A Diversity-Enhanced Memetic Algorithm For Solving Electric Vehicle Routing Problems With Time Windows And Mixed Backhauls, Jianhua Xiao, Jingguo Du, Zhiguang Cao, Xingyi Zhang, Yunyun Niu
A Diversity-Enhanced Memetic Algorithm For Solving Electric Vehicle Routing Problems With Time Windows And Mixed Backhauls, Jianhua Xiao, Jingguo Du, Zhiguang Cao, Xingyi Zhang, Yunyun Niu
Research Collection School Of Computing and Information Systems
The electric vehicle routing problem (EVRP) has been studied increasingly because of environmental concerns. However, existing studies on the EVRP mainly focus on time windows and sole linehaul customers, which might not be practical as backhaul customers are also ubiquitous in reality. In this study, we investigate an EVRP with time windows and mixed backhauls (EVRPTWMB), where both linehaul and backhaul customers exist and can be served in any order. To address this challenging problem, we propose a diversity-enhanced memetic algorithm (DEMA) that integrates three types of novel operators, including genetic operators based on adaptive selection mechanism, a selection operator …